Bootstrap Techniques For Signal Processing - Rilegato

Abdelhak M. Zoubir

Rilegato

ISBN 10: 052183127X ISBN 13: 9780521831277

Casa editrice: New Publisher, 2021

Riassunto

The statistical bootstrap is one of the methods that can be used to calculate estimates of a certain number of unknown parameters of a random process or a signal observed in noise, based on a random sample. Such situations are common in signal processing and the bootstrap is especially useful when only a small sample is available or an analytical analysis is too cumbersome or even impossible. This book covers the foundations of the bootstrap, its properties, its strengths and its limitations. The authors focus on bootstrap signal detection in Gaussian and non-Gaussian interference as well as bootstrap model selection. The theory developed in the book is supported by a number of useful practical examples written in MATLAB. The book is aimed at graduate students and engineers, and includes applications to real-world problems in areas such as radar and sonar, biomedical engineering and automotive engineering.

Su questo libro

Recensione:

'... an excellent text for a graduate level engineering course or a useful reference for those who wish to apply bootstrap techniques in their work.' Annals of Biomedical Engineering

Descrizione del libro:

The statistical bootstrap is a powerful tool in signal processing. This book covers the foundations of the bootstrap, its properties, its strengths, its limitations and model selection. The theory developed in the book is supported by a number of useful practical examples written in MATLAB.

Su questa edizione

• Editore: New Publisher
• Data di pubblicazione: 2021
• ISBN 10: 052183127X
• ISBN 13: 9780521831277
• Rilegatura: Copertina rigida
• Numero di pagine: 232